Stop guessing what your customers want and start knowing with predictive analytics—the crystal ball to unlocking a next-level customer experience.
Among marketing leaders, the benefit of predictive analytics is super obvious… Organizations have long used it to present product recommendations, cross-sells, and upsells to would-be buyers.
Surprise! Predictive analytics can be transformational for CX leaders, too.
“Predictive analytics allows us to identify opportunities and risks that might otherwise go unnoticed.”Bernard Marr (futurist)
For example, predictive analytics can be used to flag problems in the customer experience before they become apparent to customers, reduce churn, uncover bottlenecks or inefficiencies in processes, and help personalize customer service interactions by providing agents with insights into the customer’s purchase history, personality, emotions, and preferences.
Here are 3 use cases for predictive analytics in CX:
1. Proactively Flag & Resolve Customer Frustrations
By analyzing customer data, predictive analytics can identify patterns and trends that may indicate potential customer problems, allowing CX leaders to take corrective actions BEFORE customers are affected.
For example, some CX-savvy organizations use natural language processing (NLP) to analyze customer feedback and identify the root causes of customer frustrations—even if customers do not explicitly mention them.
Additionally, analysis of call center data could reveal the most common types of customer inquiries or complaints, the length of time it takes to resolve those issues, and then be used to optimize call center operations to reduce customer wait times as a result.
“Predictive analytics is the key to unlocking the hidden value in data.”Ian Ayres (economist)
2. Be Scientific About Customer Emotions
Predictive analytics also can be used to help agents understand a customer’s mood or emotional state in real-time, and then prompt them to adjust their responses accordingly. For example, if a customer is angry or frustrated, the agent can be cued to respond with empathy.
3. Map Smarter, Not Harder
Use predictive analytics to understand the typical paths that customers take along their journey, identify specific customer touchpoints that have the greatest impact on customer satisfaction, and then zero in on the customer segments that are mostly likely to churn.
As a result, organizations can design more effective retention strategies to keep these customers engaged and loyal.
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